Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory468.8 KiB
Average record size in memory48.0 B

Variable types

Text3
Categorical2

Dataset

Description보령시에 설치된 가로등 현황 데이터로 가로등 표찰 번호, 가로등이 설치된 행정동, 가로등이 설치된 지번주소, 가로등 설치 상세위치가 제공됩니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=331&beforeMenuCd=DOM_000000201001001000&publicdatapk=15088946

Alerts

데이터기준일 has constant value ""Constant

Reproduction

Analysis started2024-01-09 22:57:51.198211
Analysis finished2024-01-09 22:57:52.063621
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

표찰번호
Text

Distinct9988
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-10T07:57:52.275749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length6.0873
Min length3

Characters and Unicode

Total characters60873
Distinct characters38
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9976 ?
Unique (%)99.8%

Sample

1st row웅천읍261
2nd row대천3동068
3rd row남포면116
4th row오천면244
5th row미산면386
ValueCountFrequency (%)
101-4 2
 
< 0.1%
121-6 2
 
< 0.1%
110-3 2
 
< 0.1%
110-4 2
 
< 0.1%
110-1 2
 
< 0.1%
110-6 2
 
< 0.1%
101-9 2
 
< 0.1%
122-5 2
 
< 0.1%
101-5 2
 
< 0.1%
110-16 2
 
< 0.1%
Other values (9980) 9982
99.8%
2024-01-10T07:57:52.693908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6043
 
9.9%
3 4912
 
8.1%
2 4818
 
7.9%
면 4301
 
7.1%
천 3973
 
6.5%
5 3724
 
6.1%
4 3408
 
5.6%
0 3353
 
5.5%
6 3033
 
5.0%
- 2967
 
4.9%
Other values (28) 20341
33.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36517
60.0%
Other Letter 21359
35.1%
Dash Punctuation 2967
 
4.9%
Open Punctuation 11
 
< 0.1%
Close Punctuation 11
 
< 0.1%
Uppercase Letter 4
 
< 0.1%
Space Separator 3
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 4301
20.1%
천 3973
18.6%
대 1953
9.1%
동 1953
9.1%
주 1361
 
6.4%
청 908
 
4.3%
웅 908
 
4.3%
포 783
 
3.7%
읍 778
 
3.6%
산 731
 
3.4%
Other values (11) 3710
17.4%
Decimal Number
ValueCountFrequency (%)
1 6043
16.5%
3 4912
13.5%
2 4818
13.2%
5 3724
10.2%
4 3408
9.3%
0 3353
9.2%
6 3033
8.3%
7 2505
6.9%
9 2382
 
6.5%
8 2339
 
6.4%
Uppercase Letter
ValueCountFrequency (%)
B 2
50.0%
A 2
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 2967
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39510
64.9%
Hangul 21359
35.1%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 4301
20.1%
천 3973
18.6%
대 1953
9.1%
동 1953
9.1%
주 1361
 
6.4%
청 908
 
4.3%
웅 908
 
4.3%
포 783
 
3.7%
읍 778
 
3.6%
산 731
 
3.4%
Other values (11) 3710
17.4%
Common
ValueCountFrequency (%)
1 6043
15.3%
3 4912
12.4%
2 4818
12.2%
5 3724
9.4%
4 3408
8.6%
0 3353
8.5%
6 3033
7.7%
- 2967
7.5%
7 2505
6.3%
9 2382
 
6.0%
Other values (5) 2365
 
6.0%
Latin
ValueCountFrequency (%)
B 2
50.0%
A 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39514
64.9%
Hangul 21359
35.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6043
15.3%
3 4912
12.4%
2 4818
12.2%
5 3724
9.4%
4 3408
8.6%
0 3353
8.5%
6 3033
7.7%
- 2967
7.5%
7 2505
6.3%
9 2382
 
6.0%
Other values (7) 2369
 
6.0%
Hangul
ValueCountFrequency (%)
면 4301
20.1%
천 3973
18.6%
대 1953
9.1%
동 1953
9.1%
주 1361
 
6.4%
청 908
 
4.3%
웅 908
 
4.3%
포 783
 
3.7%
읍 778
 
3.6%
산 731
 
3.4%
Other values (11) 3710
17.4%

행정동
Categorical

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
대천5동
1404 
웅천읍
1140 
대천4동
840 
오천면
795 
남포면
761 
Other values (11)
5060 

Length

Max length4
Median length3
Mean length3.3779
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row웅천읍
2nd row대천3동
3rd row남포면
4th row오천면
5th row미산면

Common Values

ValueCountFrequency (%)
대천5동 1404
14.0%
웅천읍 1140
11.4%
대천4동 840
 
8.4%
오천면 795
 
8.0%
남포면 761
 
7.6%
주교면 658
 
6.6%
청라면 651
 
6.5%
대천3동 627
 
6.3%
대천1동 526
 
5.3%
천북면 471
 
4.7%
Other values (6) 2127
21.3%

Length

2024-01-10T07:57:52.823935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대천5동 1404
14.0%
웅천읍 1140
11.4%
대천4동 840
 
8.4%
오천면 795
 
8.0%
남포면 761
 
7.6%
주교면 658
 
6.6%
청라면 651
 
6.5%
대천3동 627
 
6.3%
대천1동 526
 
5.3%
천북면 471
 
4.7%
Other values (6) 2127
21.3%

지번주소
Text

Distinct7300
Distinct (%)73.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-10T07:57:53.154397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length11.1642
Min length4

Characters and Unicode

Total characters111642
Distinct characters132
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6274 ?
Unique (%)62.7%

Sample

1st row웅천읍 관당리 산124-5
2nd row동대동 1341
3rd row남포면 월전리 561-4
4th row오천면 소성리 615
5th row미산면 평라리 684-8
ValueCountFrequency (%)
웅천읍 1139
 
4.3%
신흑동 910
 
3.5%
오천면 795
 
3.0%
남포면 761
 
2.9%
대천동 680
 
2.6%
주교면 658
 
2.5%
명천동 653
 
2.5%
청라면 651
 
2.5%
동대동 477
 
1.8%
천북면 471
 
1.8%
Other values (5643) 19171
72.7%
2024-01-10T07:57:53.592572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16461
 
14.7%
- 6896
 
6.2%
1 6879
 
6.2%
리 6221
 
5.6%
2 5549
 
5.0%
면 5082
 
4.6%
동 4588
 
4.1%
3 4175
 
3.7%
천 3955
 
3.5%
4 3679
 
3.3%
Other values (122) 48157
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49805
44.6%
Decimal Number 38480
34.5%
Space Separator 16461
 
14.7%
Dash Punctuation 6896
 
6.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 6221
 
12.5%
면 5082
 
10.2%
동 4588
 
9.2%
천 3955
 
7.9%
산 2074
 
4.2%
주 1982
 
4.0%
대 1594
 
3.2%
신 1248
 
2.5%
읍 1185
 
2.4%
청 1162
 
2.3%
Other values (110) 20714
41.6%
Decimal Number
ValueCountFrequency (%)
1 6879
17.9%
2 5549
14.4%
3 4175
10.8%
4 3679
9.6%
5 3477
9.0%
6 3206
8.3%
7 3114
8.1%
8 3006
7.8%
9 2942
7.6%
0 2453
 
6.4%
Space Separator
ValueCountFrequency (%)
16461
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6896
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61837
55.4%
Hangul 49805
44.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 6221
 
12.5%
면 5082
 
10.2%
동 4588
 
9.2%
천 3955
 
7.9%
산 2074
 
4.2%
주 1982
 
4.0%
대 1594
 
3.2%
신 1248
 
2.5%
읍 1185
 
2.4%
청 1162
 
2.3%
Other values (110) 20714
41.6%
Common
ValueCountFrequency (%)
16461
26.6%
- 6896
11.2%
1 6879
11.1%
2 5549
 
9.0%
3 4175
 
6.8%
4 3679
 
5.9%
5 3477
 
5.6%
6 3206
 
5.2%
7 3114
 
5.0%
8 3006
 
4.9%
Other values (2) 5395
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61837
55.4%
Hangul 49805
44.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16461
26.6%
- 6896
11.2%
1 6879
11.1%
2 5549
 
9.0%
3 4175
 
6.8%
4 3679
 
5.9%
5 3477
 
5.6%
6 3206
 
5.2%
7 3114
 
5.0%
8 3006
 
4.9%
Other values (2) 5395
 
8.7%
Hangul
ValueCountFrequency (%)
리 6221
 
12.5%
면 5082
 
10.2%
동 4588
 
9.2%
천 3955
 
7.9%
산 2074
 
4.2%
주 1982
 
4.0%
대 1594
 
3.2%
신 1248
 
2.5%
읍 1185
 
2.4%
청 1162
 
2.3%
Other values (110) 20714
41.6%

상세위치
Text

Distinct426
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-10T07:57:53.844754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length7
Mean length7.0158
Min length1

Characters and Unicode

Total characters70158
Distinct characters364
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique283 ?
Unique (%)2.8%

Sample

1st row주소와 동일함
2nd row주소와 동일함
3rd row주소와 동일함
4th row주소와 동일함
5th row주소와 동일함
ValueCountFrequency (%)
주소와 8989
47.3%
동일함 8989
47.3%
명천택지개발지구 71
 
0.4%
화산교차로상부도로 32
 
0.2%
원산안면대교 31
 
0.2%
백사장가로등 18
 
0.1%
원의교차로 16
 
0.1%
남포방조제도로 15
 
0.1%
웅천사격장이주단지 15
 
0.1%
남포궁촌간도로sk주유소옆 15
 
0.1%
Other values (422) 812
 
4.3%
2024-01-10T07:57:54.194111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 9158
13.1%
동 9050
12.9%
소 9037
12.9%
9004
12.8%
일 9003
12.8%
와 8992
12.8%
함 8989
12.8%
로 263
 
0.4%
장 235
 
0.3%
교 226
 
0.3%
Other values (354) 6201
8.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60896
86.8%
Space Separator 9004
 
12.8%
Uppercase Letter 122
 
0.2%
Decimal Number 108
 
0.2%
Open Punctuation 11
 
< 0.1%
Close Punctuation 11
 
< 0.1%
Dash Punctuation 5
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 9158
15.0%
동 9050
14.9%
소 9037
14.8%
일 9003
14.8%
와 8992
14.8%
함 8989
14.8%
로 263
 
0.4%
장 235
 
0.4%
교 226
 
0.4%
지 198
 
0.3%
Other values (323) 5745
9.4%
Uppercase Letter
ValueCountFrequency (%)
S 37
30.3%
K 36
29.5%
G 10
 
8.2%
C 7
 
5.7%
I 5
 
4.1%
N 5
 
4.1%
M 4
 
3.3%
L 4
 
3.3%
J 3
 
2.5%
U 3
 
2.5%
Other values (6) 8
 
6.6%
Decimal Number
ValueCountFrequency (%)
1 32
29.6%
0 27
25.0%
2 16
14.8%
4 11
 
10.2%
3 8
 
7.4%
5 7
 
6.5%
7 3
 
2.8%
8 2
 
1.9%
6 1
 
0.9%
9 1
 
0.9%
Space Separator
ValueCountFrequency (%)
9004
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60896
86.8%
Common 9140
 
13.0%
Latin 122
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 9158
15.0%
동 9050
14.9%
소 9037
14.8%
일 9003
14.8%
와 8992
14.8%
함 8989
14.8%
로 263
 
0.4%
장 235
 
0.4%
교 226
 
0.4%
지 198
 
0.3%
Other values (323) 5745
9.4%
Latin
ValueCountFrequency (%)
S 37
30.3%
K 36
29.5%
G 10
 
8.2%
C 7
 
5.7%
I 5
 
4.1%
N 5
 
4.1%
M 4
 
3.3%
L 4
 
3.3%
J 3
 
2.5%
U 3
 
2.5%
Other values (6) 8
 
6.6%
Common
ValueCountFrequency (%)
9004
98.5%
1 32
 
0.4%
0 27
 
0.3%
2 16
 
0.2%
4 11
 
0.1%
( 11
 
0.1%
) 11
 
0.1%
3 8
 
0.1%
5 7
 
0.1%
- 5
 
0.1%
Other values (5) 8
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60896
86.8%
ASCII 9262
 
13.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 9158
15.0%
동 9050
14.9%
소 9037
14.8%
일 9003
14.8%
와 8992
14.8%
함 8989
14.8%
로 263
 
0.4%
장 235
 
0.4%
교 226
 
0.4%
지 198
 
0.3%
Other values (323) 5745
9.4%
ASCII
ValueCountFrequency (%)
9004
97.2%
S 37
 
0.4%
K 36
 
0.4%
1 32
 
0.3%
0 27
 
0.3%
2 16
 
0.2%
4 11
 
0.1%
( 11
 
0.1%
) 11
 
0.1%
G 10
 
0.1%
Other values (21) 67
 
0.7%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-09-25
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-25
2nd row2023-09-25
3rd row2023-09-25
4th row2023-09-25
5th row2023-09-25

Common Values

ValueCountFrequency (%)
2023-09-25 10000
100.0%

Length

2024-01-10T07:57:54.315367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:57:54.392622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-25 10000
100.0%

Missing values

2024-01-10T07:57:51.929652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:57:52.020782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

표찰번호행정동지번주소상세위치데이터기준일
11517웅천읍261웅천읍웅천읍 관당리 산124-5주소와 동일함2023-09-25
6736대천3동068대천3동동대동 1341주소와 동일함2023-09-25
4707남포면116남포면남포면 월전리 561-4주소와 동일함2023-09-25
10049오천면244오천면오천면 소성리 615주소와 동일함2023-09-25
9064미산면386미산면미산면 평라리 684-8주소와 동일함2023-09-25
16186청소면604청소면청소면 죽림리 188주소와 동일함2023-09-25
8019대천5동297대천5동요암동 974주소와 동일함2023-09-25
967153-16대천5동신흑동 산205-108주소와 동일함2023-09-25
5304남포면736남포면남포면 봉덕리 495-73주소와 동일함2023-09-25
1117163-3대천5동신흑동 2204-16해수욕장사업소주차장2023-09-25
표찰번호행정동지번주소상세위치데이터기준일
4859남포면289남포면남포면 달산리 935-2주소와 동일함2023-09-25
3703364-28대천4동명천동 322-3주소와 동일함2023-09-25
7104대천3동437대천3동동대동 672-84주소와 동일함2023-09-25
1085160-3대천5동신흑동 1724-2주소와 동일함2023-09-25
11041웅천읍028웅천읍웅천읍 독산리 774주소와 동일함2023-09-25
3153336-9청라면청라면 향천리 886주소와 동일함2023-09-25
9298성주면054성주면성주면 개화리 365-18주소와 동일함2023-09-25
12969주교면750대천2동대천동 1199-1주소와 동일함2023-09-25
2455268-13대천5동요암동 404-1주소와 동일함2023-09-25
8520대천5동822대천5동남곡동 847-15주소와 동일함2023-09-25